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- Tasks: Design and build AI-powered systems to solve real-world problems in energy and utilities.
- Company: Join a leading tech company transforming the energy sector for a sustainable future.
- Benefits: Enjoy competitive salary, flexible working, and opportunities for professional growth.
- Why this job: Make a meaningful impact on global energy solutions while working with cutting-edge technology.
- Qualifications: Strong experience in machine learning, Python, and cloud infrastructure.
- Other info: Be part of a dynamic team with a culture of learning and collaboration.
The predicted salary is between 48000 - 84000 £ per year.
Help us use technology to make a big green dent in the universe. Kraken powers some of the most innovative global developments in energy. We’re a technology company focused on creating a smart, sustainable energy system. From optimising renewable generation, creating a more intelligent grid and enabling utilities to provide excellent customer experiences, our operating system for energy is transforming the industry around the world in a way that benefits everyone. It’s a really exciting time in energy.
Our tech platform ‘Kraken’ is already licensed to support 55 million customer accounts globally, and we aim to serve 100 million by 2027. Kraken is the most AI-driven, innovative, forward-thinking platform for energy management. We’re now charging the Kraken platform to other utility industries (Water and Broadband) and have created a new team called Kraken Utilities. Over the last 3 years we have built this team from scratch to re-architect, design, and develop our Kraken software platform to solve complex industry-wide problems within the water and broadband sectors.
We’re in a very exciting growth phase, and have already signed six key clients: Severn Trent, Leep, Portsmouth Water, Essential Energy, TalkTalk, and Cuckoo. We are currently 120+ people strong globally.
We are building out our Machine Learning & AI capability within Kraken Utilities and are looking for a Senior Machine Learning Engineer to help design, build and scale ML-powered products already running in production. This is a hands-on, product-focused role. You will work closely with product managers, designers, software engineers and other ML practitioners, contribute to technical direction and best practices, and take ownership of complex problems across our suite of AI and ML products.
What You’ll Do:- Design, build and deploy machine-learning and AI-powered systems that solve real business and customer problems.
- Work end-to-end: from data exploration and experimentation through to production deployment, monitoring and iteration.
- Collaborate closely with product managers and engineers to shape solutions that are practical, scalable and maintainable.
- Lead deep technical investigations into complex or ambiguous problems, including critical bugs across multiple systems.
- Help define and improve ML and engineering best practices within the team.
- Run and analyse experiments (e.g. A/B tests) to validate product and model improvements.
- Stay up to date with advances in ML, GenAI and developer tooling, and apply them thoughtfully to our products.
- Contribute to a culture of learning through knowledge sharing, internal talks and mentoring.
- Strong hands-on experience applying machine learning in production environments with a proven track record of writing maintainable, testable code in complex codebases.
- Excellent Python skills and solid SQL experience. Deep understanding of ML fundamentals: data analysis, model selection, evaluation, deployment and monitoring.
- Experience working with ML / data libraries such as pandas, NumPy, scikit-learn, PyTorch or TensorFlow.
- Comfort working in a software-engineering-heavy environment (version control, CI/CD, code reviews, MLOps principles).
- Experience building and operating systems on cloud infrastructure (AWS preferred).
- Ability to clearly explain technical concepts and trade-offs to a wide range of stakeholders.
- Confidence working autonomously, asking questions early, and collaborating across teams and with clients.
- Experience building GenAI or NLP-based products.
- Exposure to LLM tooling, prompting, agents or evaluation techniques.
- Experience with Kubernetes, dbt, or modern data tooling.
- Experience running production experiments (A/B testing).
- Experience mentoring junior colleagues and leading workstreams.
We care more about how you think, learn and apply your skills than about a specific number of years of experience.
Tech Stack:- Languages: Python, SQL
- ML / Data: pandas, NumPy, scikit-learn, PyTorch, TensorFlow, NLP tooling
- Backend: Django, Django REST Framework, GraphQL
- Cloud & Ops: AWS, CI/CD, Datadog, CloudWatch
- Data: Postgres, Databricks
- Client: React, htmx
- AI Tooling: ChatGPT, Claude, Gemini, Cursor
- Two-week sprints with planning and delivery tracked in Asana.
- Daily stand-ups, async collaboration via Slack, and regular knowledge-sharing sessions.
- Strong emphasis on autonomy, trust and a no-blame culture.
- Regular collaboration with other ML and platform teams across Kraken.
We would prefer someone who can work in our London office on a hybrid remote policy of 1-2 days a week onsite. You do need to be able to work in the UK.
We’re very excited to be growing our team. If you’re reading this and grinning, please apply! There are huge challenges to tackle, and we need amazing people who are keen to get stuck in.
As an equal opportunity employer, we do not discriminate on the basis of any protected attribute. Our Applicant and Candidate Privacy Notice and AI Notice govern the collection and use of your personal data in connection with your application and use of our website.
Senior Machine Learning Engineer - Utilities in London employer: Kraken
Contact Detail:
Kraken Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer - Utilities in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with current Kraken employees on LinkedIn. A friendly chat can sometimes lead to opportunities that aren’t even advertised!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects or contributions to open-source. This gives us a tangible sense of what you can bring to the table beyond just your CV.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge and be ready to discuss your past experiences. We love candidates who can articulate their thought process and problem-solving skills.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at Kraken.
We think you need these skills to ace Senior Machine Learning Engineer - Utilities in London
Some tips for your application 🫡
Show Your Passion for Sustainability: When writing your application, let your enthusiasm for creating a sustainable future shine through. We’re all about making a big green dent in the universe, so share how your skills and experiences align with our mission at Kraken.
Tailor Your Experience: Make sure to highlight your hands-on experience with machine learning and software engineering. We want to see how you’ve tackled real-world problems, so be specific about your projects and the impact they had.
Be Clear and Concise: Keep your application straightforward and to the point. Use clear language to explain your technical skills and experiences, as we value the ability to communicate complex ideas effectively across teams.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity to join our growing team at Kraken!
How to prepare for a job interview at Kraken
✨Know Your ML Fundamentals
Brush up on your machine learning fundamentals, especially around data analysis, model selection, and deployment. Be ready to discuss how you've applied these concepts in real-world scenarios, as this will show your hands-on experience and understanding of the full ML lifecycle.
✨Showcase Your Coding Skills
Prepare to demonstrate your Python and SQL skills during the interview. You might be asked to solve coding problems or explain your approach to writing maintainable and testable code. Familiarise yourself with libraries like pandas and TensorFlow, as they are crucial for the role.
✨Understand the Business Impact
Be ready to discuss how your work in machine learning can solve real business problems and enhance customer experiences. Think about specific examples where your ML solutions have made a difference, and be prepared to articulate the value you bring to the team.
✨Collaborate and Communicate
Since the role involves working closely with product managers and engineers, practice explaining technical concepts in simple terms. Highlight your collaborative experiences and how you've contributed to team success, as strong communication skills are key in this environment.
